AI Program KPIs & Metrics Guide

Overview

AI governance programs need to demonstrate effectiveness—to executives, boards, regulators, and stakeholders. "We're doing governance" isn't sufficient; you need metrics showing coverage, risk reduction, process efficiency, and value delivery.

This guide provides a comprehensive metrics framework for AI governance. Select metrics relevant to your program maturity and reporting needs; use targets as benchmarks to measure progress.

What's Inside

1. Program Coverage Metrics

• AI System Inventory Coverage (% documented) — Target: 100%
• High-Risk Systems Under Governance (%) — Target: 100%
• Business Unit Participation (% with liaison) — Target: 100%
• Vendor Coverage (% with due diligence) — Target: 100%
• Policy Acknowledgment Rate (%) — Target: ≥95%

2. Risk & Compliance Metrics

• Risk Assessments Complete (%) — Target: 100%
• Open High-Risk Findings (#) — Target: 0
• Average Risk Remediation Time (days) — Target: ≤30 days
• Bias Testing Compliance (%) — Target: 100%
• Regulatory Compliance Score (%) — Target: 100%
• Audit Findings (#/year) — Target: ≤2

3. Process Efficiency Metrics

• Project Intake Cycle Time (days)
• Risk Assessment Turnaround (days)
• Vendor Assessment Turnaround (days)
• Exception Request Processing (days)
• Governance Committee Throughput (decisions/quarter)

4. Incident Management Metrics

• AI Incidents (# by severity)
• Mean Time to Detect (MTTD)
• Mean Time to Resolve (MTTR)
• Incidents Resolved Within SLA (%)
• Recurring Incidents (%)
• Root Cause Analysis Completion (%)

5. Training & Culture Metrics

• Training Completion Rate (%) — Target: ≥95%
• Assessment Pass Rate (%)
• Awareness Survey Scores
• Policy Questions Submitted (#)
• Reported Concerns (#)

6. Value & ROI Metrics

• AI Value Delivered ($)
• Cost Avoidance from Risk Prevention ($)
• Compliance Cost Savings ($)
• Project Acceleration (days saved)
• Governance ROI (value/cost)

Each metric includes:

• Clear definition
• Target benchmark
• Data source
• Reporting frequency (weekly, monthly, quarterly)

Who This Is For

• Chief AI Officers establishing program metrics
• AI Governance Managers tracking performance
• Executive Sponsors reviewing program effectiveness
• Board Committees overseeing AI governance
• Audit/Compliance assessing program maturity

Why This Resource

Starting from scratch with metrics takes trial and error—what to measure, what targets are reasonable, where to get data. This guide provides a comprehensive starting point based on governance best practices. Select metrics relevant to your program; adjust targets based on your maturity level.

The six-category structure ensures balanced measurement—not just activity metrics but outcomes and value.

FAQ

Q: Which metrics should we start with?

A: Start with Program Coverage (do you know what AI you have?) and Risk & Compliance (are risks being assessed?). Add Process Efficiency and Incident Management as the program matures. Value & ROI metrics require baseline data to measure improvement.

Q: What if we can't hit these targets?

A: Targets represent mature program benchmarks. Set interim targets based on your current state; use the guide targets as long-term goals.

Q: How do we get data for these metrics?

A: Each metric lists data sources (AI Registry, Risk Tracker, LMS, etc.). If you don't have these systems yet, the metrics guide what data to start capturing.